Using data analytics and advanced algorithms, DXC and the Singapore General Hospital (SGH) are working on an AI solution that can guide a doctor in prescribing antibiotics. This solution has recently been recognized as one of the most impactful projects, by the Ministry of Health, Singapore at the "National Health Tech Challenge" awards.Humanoid Robotics for Digital Collaboration – Using advanced mobile applications and humanoid robotics technologies, this DXC solution highlights the future of digital collaboration between enterprises, customers and other stakeholders relevant to the insurance industry today. Supported by the application of machine learning/artificial intelligence (ML/AI), the humanoid robot agent helps banks or wealth managers recommend and sell insurance solutions personalized for each customer. It also allows insurers to interact and complete the insurance solutions sale process through this platform. The interaction is directly with the customer, thereby giving transparent and authentic data based on vital image statistics from the robot.

In this paper we investigate panel regression models with interactive fixed effects. We propose two new estimation methods that are based on minimizing convex objective functions. The first method minimizes the sum of squared residuals with a nuclear (trace) norm regularization. The second method minimizes the nuclear norm of the residuals. We establish the consistency of the two resulting estimators. Those estimators have a very important computational advantage compared to the existing least squares (LS) estimator, in that they are defined as minimizers of a convex objective function. In addition, the nuclear norm penalization helps to resolve a potential identification problem for interactive fixed effect models, in particular when the regressors are low-rank and the number of the factors is unknown. We also show how to construct estimators that are asymptotically equivalent to the least squares (LS) estimator in Bai (2009) and Moon and Weidner (2017) by using our nuclear norm regularized or minimized estimators as initial values for a finite number of LS minimizing iteration steps. This iteration avoids any non-convex minimization, while the original LS estimation problem is generally non-convex, and can have multiple local minima.

Multi-Criteria Decision Analysis (MCDA) methods are widely used in various fields and disciplines. While most of the research has been focused on the development and improvement of new MCDA methods, relatively limited attention has been paid to their appropriate selection for the given decision problem. Their improper application decreases the quality of recommendations, as different MCDA methods deliver inconsistent results. The current paper presents a methodological and practical framework for selecting suitable MCDA methods for a particular decision situation. A set of 56 available MCDA methods was analyzed and, based on that, a hierarchical set of methods characteristics and the rule base were obtained. This analysis, rules and modelling of the uncertainty in the decision problem description allowed to build a framework supporting the selection of a MCDA method for a given decision-making situation. The practical studies indicate consistency between the methods recommended with the proposed approach and those used by the experts in reference cases. The results of the research also showed that the proposed approach can be used as a general framework for selecting an appropriate MCDA method for a given area of decision support, even in cases of data gaps in the decision-making problem description. The proposed framework was implemented within a web platform available for public use at www.mcda.it.

Henry Ford revolutionized the automobile industry--and manufacturing in general--with the concept of the assembly line. Vehicles existed and were being manufactured before Ford introduced the assembly line but streamlining and automating the manufacturing process allowed vehicles to be produced significantly faster. The world of cybersecurity is at a similar impasse and facing a similar revolution in terms of speed--thanks to machine learning (ML) and artificial intelligence (AI). The concepts of vulnerability scanning and vulnerability management are not new. The idea that organizations need to monitor application activity and behavior to identify indicators of compromise and detect suspicious or malicious activity is also relatively common.

To what extent can your doctor's functions be automated -- replaced or enhanced by intelligent machines? How might such automation improve care and reduce costs? These questions are central to understanding Clover Health -- a California-based company providing Medicare Advantage insurance plans in seven states: New Jersey, Pennsylvania, Tennessee, Georgia, Arizona, South Carolina and Texas. A while back, I hosted a dinner in New York for a dozen-plus health care innovators -- entrepreneurs, medical school professors, futurists, etc. Someone in the room asked, "How much of today's physician services can be reduced to algorithms?" An algorithm is a set of instructions (like a computer program) leading to unambiguous results.

Artificial intelligence tools are only as good as the data they're built on, and it's critical agencies keep that in mind as they ramp up funding for the emerging tech, according to the government's top technologist. "If we don't make the right investments [on] the data side, it's like we have the fastest plane in the world and no fuel," said federal Chief Information Officer Suzette Kent on Wednesday. Artificial intelligence has the potential to improve citizen services, kickstart the economy and create a more efficient government, and AI innovation remains "a priority of this entire administration," Kent told the crowd at NVIDIA's GTC DC conference. But AI initiatives will only be successful if agencies first understand the data at their fingertips, she said. "Getting [data] organized and accessible for AI is no simple task," she said.

Docked in Lewes, Delaware, is a 166-foot ship called the DELRIVER that is rarely called out of port. Nonetheless, it's staffed 24/7 by a four-person crew and stands ready for action at a moment's notice. The DELRIVER is an oil-spill response vessel, funded by the local oil industry to clean up spills in the Delaware Bay as soon as they happen. The last major spill in the area was in 2004, when the tanker Athos spewed 265,000 gallons of heavy crude from Venezuela into the Delaware River. The last spill of any kind that it responded to was a small diesel spill in 2014.

NASA has released a jaw-dropping video of the moment its deluge system dumps thousands of gallons of water onto Launch Pad 39B at the Kennedy Space Center. The space agency is prepping for the maiden voyage of the $8.9 billion Space Launch System (SLS) rocket, which will require roughly 450,000 gallons of water during ignition and liftoff to counteract the extreme heat and acoustics. In the incredible footage from this month's wet flow test, a torrential stream of water can be seen spewing straight up into the air and washing over the complex before dwindling to a trickle in just a matter of seconds. The latest wet flow test, shown in the footage above, was conducted on October 15 at the Kennedy Space Center's Launch Pad 39B. The SLS rocket will lift off with 8.4 million pounds of thrust, thanks to its four RS-25 engines and two solid rocket boosters.

NASA has spotted a second perfectly rectangular iceberg in the Antarctic. The second rectangular berg, known as a'tabular' iceberg, was spotted off the east coast of the Antarctic Peninsula, near the Larsen C ice shelf and close to the first one. It is part of a large'field of bergs NASA experts may have recently broken off the shelf, and say the sharp angles and flat surfaces are evidence the break occurred very recently. Just past the original rectangular iceberg, which is visible from behind the outboard engine, IceBridge saw another relatively rectangular berg and the A68 iceberg in the distance. Tabular icebergs split off the edges of ice shelves in the same way a fingernail that grows too long ends up cracking off.

A'shocking' discovery in Pompeii has found the undisturbed skeletons of five people who tried to take refuge from the eruption of Mount Vesuvius in A.D.79. It is believe the five, two women and three children, sought safety in a small room - but were either crushed when the roof caved in or burned. The house where they were found has revealed a string of discoveries in recent weeks - from stunning murals to an inscription that revealed the eruption was earlier than thought. The remains of five people, probably two women and three children, were found in a during excavations in Pompeii, Italy, 24 October 2018. The director of the Pompeii archaeological site, Massimo Osanna, called it'a shocking find, but also very important for history.'